In the related art, a diagnosis has been performed using a medical image such as a Computed Tomography (CT) image, a Magnetic Resonance (MR) image, or an Ultrasound (US) image. In addition, various image processing methods for extracting an observation target part or removing an unnecessary region from the medical image so as to create an image suitable for the diagnosis have been proposed. Further, a computer aided diagnosis device called Computer Aided Diagnosis (CAD) for detecting abnormal shadows from a medical image has been developed. As above, a plurality of processing algorithms corresponding to various processing purposes for a medical image have been developed.
However, a medical image shows different features depending on a scanning part or the kind of examination. For this reason, to perform a processing in a different process depending on parts achieves good efficiency even in the same processing purpose. For example, when an abnormal shadow is detected from a medical image, a different abnormal shadow detection algorithm is applied depending on a scanning part or diagnosis content. For example, the head and the abdomen employ different abnormal shadow detection algorithms. As a device for selecting an abnormal shadow detection algorithm appropriate for a medical image, for example, an abnormal shadow detection device disclosed in PTL 1 has been proposed.
PTL 1 discloses an abnormal shadow detection device which stores an abnormal shadow detection algorithm for each part of an object, and, when an abnormal shadow is detected from a medical image, creates a set of tomographic images of the anatomically same part which is scanned at different dates and times, obtains a difference between the tomographic images of each set, identifies an object part of the tomographic image, and selects and applies an abnormal shadow detection algorithm for and to the identified part.